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<p>Radio frequency (RF) low-temperature plasmas are essential for industrial processes like semiconductor fabrication and material processing, due to their ability to deliver reactive species for precise surface treatment. Efficient power transfer from the RF source to the plasma requires advanced impedance matching networks (IMNs). This review summarizes recent progress in circuit design, power systems, and control strategies, emphasizing their effects on plasma control and novel applications. We examine the evolution of plasma-circuit models from lumped element to distributed circuit models coupling with particle-in-cell/Monte Carlo collision and nonlinear transmission line models, highlighting their respective advantages. Self-consistent models that couple plasma dynamics with circuit equations are discussed as powerful tools for design and optimization. We also highlight insights into the nonlinear interaction between IMNs and plasma, as well as the emerging use of machine learning, for optimizing impedance matching. Finally, the critical role of RF coaxial cables as transmission lines influencing impedance and power delivery is addressed.</p>

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Tailoring external circuitry for enhanced control of RF low-temperature plasmas: advances and opportunities

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Ya Zhang,
  • Jingwen Xu,
  • Shimin Yu,
  • Zhili Chen,
  • Lifen Zhao,
  • Dehen Cao,
  • Wei Jiang,
  • Zhipeng Chen,
  • Zhijiang Wang

摘要

Radio frequency (RF) low-temperature plasmas are essential for industrial processes like semiconductor fabrication and material processing, due to their ability to deliver reactive species for precise surface treatment. Efficient power transfer from the RF source to the plasma requires advanced impedance matching networks (IMNs). This review summarizes recent progress in circuit design, power systems, and control strategies, emphasizing their effects on plasma control and novel applications. We examine the evolution of plasma-circuit models from lumped element to distributed circuit models coupling with particle-in-cell/Monte Carlo collision and nonlinear transmission line models, highlighting their respective advantages. Self-consistent models that couple plasma dynamics with circuit equations are discussed as powerful tools for design and optimization. We also highlight insights into the nonlinear interaction between IMNs and plasma, as well as the emerging use of machine learning, for optimizing impedance matching. Finally, the critical role of RF coaxial cables as transmission lines influencing impedance and power delivery is addressed.